SOTAVerified

Graph Generation

Graph Generation is an important research area with significant applications in drug and material designs.

Source: Graph Deconvolutional Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 601–610 of 712 papers

TitleStatusHype
Cascading Large Language Models for Salient Event Graph GenerationCode0
Towards Addressing the Misalignment of Object Proposal Evaluation for Vision-Language Tasks via Semantic GroundingCode0
On-Demand and Lightweight Knowledge Graph Generation -- a Demonstration with DBpediaCode0
OG-SGG: Ontology-Guided Scene Graph Generation. A Case Study in Transfer Learning for Telepresence RoboticsCode0
Non-isomorphic Inter-modality Graph Alignment and Synthesis for Holistic Brain MappingCode0
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion ModelsCode0
Node Embedding via Word Embedding for Network Community DiscoveryCode0
NetGAN: Generating Graphs via Random WalksCode0
Understanding the Representation Power of Graph Neural Networks in Learning Graph TopologyCode0
Natural Language Processing for Music Knowledge DiscoveryCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RNNStreetMover0.03—Unverified
2GraphRNNStreetMover0.02—Unverified
3GGT without CAStreetMover0.02—Unverified
4GGTStreetMover0.02—Unverified